De jure and de facto property tax rates in large US cities

Scholars and policymakers have long been interested in measuring the relative property tax burden across cities. Most existing estimates rely on statutory rates and other official metrics to compute the prevailing tax rate in a city. Yet, a crucial feature of the property tax is that it is levied on estimated values rather than transaction prices. Without accounting for the quality of the estimated values it is impossible to know the effective tax rate. In this paper, I compute effective tax rates from micro data on property sales, aligning the tax due in the sale year with the sale price. I compare the observed effective tax rates with the best available estimates based on official sources. Relative to prior estimates, I find that effective tax rates are (a) generally lower, due to lags in estimated values; (b) widely varying even within the same city, due to errors in estimated values; and (c) usually regressive, due to biases in estimated values. I discuss the implications of these findings for taxpayers and policymakers.